How can I design the input layer of a feed-forward neural network to be trained with a medical dataset with three features?
I would give some advice here:

You should probably use Convolutional Neural Network for image data or you'll end up with too many input features, and too much computation. What are your constraints on this point?

I would not mix image data with numerical data. Maybe you can implement two neural networks, one handling image data and another managing the numerical data, each one outputting their results. A second step would be to use their results to handcraft a global result or let another NN manage this.